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Southern forests contribute significantly to the carbon sink for the atmospheric carbon dioxide (CO2) associated with the anthropogenic activities in the United States. Natural disasters like hurricanes are constantly threatening these forests. Hurricane winds can have a destructive impact on natural vegetation and can adversely impact net primary productivity (NPP). Hurricane Katrina (23-30 August 2005), one of the most destructive natural disasters in history, has affected the ecological balance of the Gulf Coast. This study analyzed the impacts of different categories of sustained winds of Hurricane Katrina on NPP in Mississippi. The study used the Carnegie-Ames-Stanford Approach (CASA) model to estimate NPP by using remote sensing data. The results indicated that NPP decreased by 14% in the areas hard hit by category 3 winds and by 1% in the areas hit by category 2 winds. However, there was an overall increase in NPP, from 2005 to 2006 by 0.60 Tg of carbon, in Mississippi. The authors found that Pearl River, Stone, Hancock, Jackson, and Harrison counties in Mississippi faced significant depletion of NPP because of Hurricane Katrina. [ABSTRACT FROM AUTHOR]

The Advanced Collaborative Emissions Study (ACES) program required the use of representative heavy-duty diesel engine activity. This need resulted in an engine test schedule creation program, and a schedule of engine modes representative of modern truck usage was developed based on data collected from engines in trucks operated through the heavy heavy-duty diesel truck (HHDDT) chassis schedule. The ACES test schedule included four active modes of truck operation including creep, transient, cruise, and high-speed cruise (HHDDT_S). This paper focuses on Phase 2 of the program, which was to validate and demonstrate the use of the ACES modes in a test cell. Preliminary testing was performed using a 1992 Detroit Diesel Corporation heavy heavy-duty diesel engine (HHDDE) on only the transient mode. On the basis of these results, each mode was modified slightly to suit implementation in a test cell. The locations of "closed throttle" points in the modes were determined through careful examination of the data. These closed throttle points were simulated during testing by adding negative set point torque values to the input file. After modification, all modes were tested during a final ACES modes demonstration period using a 2004 Cummins ISM HHDDE, obtaining three runs for each mode. During testing, carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx), particulate matter (PM), and hydrocarbon (HC) emissions were measured, and engine control unit (ECU) data were recorded. The new ACES modes did not adopt the Federal Test Procedure (FTP) regression criteria. New regression criteria for acceptability of a run were determined for each mode using the data obtained during testing. [ABSTRACT FROM AUTHOR]

This paper presents an energy and environmental network analysis model to explore tradeoffs associated with freight transport. The geospatial model uses an intermodal network built by the authors to connect various modes (rail, road, water) via intermodal terminals. Routes along the network are characterized not only by temporal and distance attributes, but also by cost, energy, and emissions attributes (including emissions of carbon dioxide, particulate matter, sulfur oxides, volatile organic compounds, and oxides of nitrogen). Decision-makers can use the model to explore tradeoffs among alternative route selection across different modal combinations, and to identify optimal routes for objectives that feature energy and environmental parameters (e.g., minimize carbon dioxide emissions). The model is demonstrated with three case studies of freight transport along the U.S. eastern seaboard. [ABSTRACT FROM AUTHOR]

Abstract: Typical top-down regional assessments of CO2 storage feasibility are sufficient for determining the maximum volumetric capacity of deep saline aquifers. However, they do not reflect the regional economic feasibility of storage. This is controlled, in part, by the number and type of injection wells that are necessary to achieve regional CO2 storage goals. In contrast, the geomechanics-based assessment workflow that we present in this paper follows a bottom-up approach for evaluating regional deep saline aquifer CO2 storage feasibility. The CO2 storage capacity of an aquifer is a function of its porous volume as well as its CO2 injectivity. For a saline aquifer to be considered feasible in this assessment it must be able to store a specified amount of CO2 at a reasonable cost per ton of CO2. The proposed assessment workflow has seven steps that include (1) defining the storage project and goals, (2) characterizing the geology and developing a geomechanical model of the aquifer, (3) constructing 3D aquifer models, (4) simulating CO2 injection, (5,6) evaluating CO2 injection and storage feasibility (with and without injection well stimulation), and (7) determining whether it is economically feasible to proceed with the storage project. The workflow was applied to a case study of the Rose Run sandstone aquifer in the Eastern Ohio River Valley, USA. We found that it is feasible in this region to inject 113MtCO2/year for 30 years at an associated well cost of less than US $1.31/tCO2, but only if injectivity enhancement techniques such as hydraulic fracturing and injection induced micro-seismicity are implemented. [Copyright &y& Elsevier]

Abstract: This paper investigates injection of CO2 into non-dome-shaped geological structures that do not provide the traps traditionally deemed necessary for the development of artificial CO2 reservoirs. We have developed a conceptual and two numerical models of the geology and groundwater along a cross-section lying approximately NW–SE and in the vicinity of the Hunter power station on the Colorado Plateau, Central Utah and identified a number of potential sequestration sites on this cross-section. Preliminary modeling identified the White Rim Sandstone as appearing to offer the properties required of a successful sequestration site. Detailed modeling of injection of CO2 into the White Rim Sandstone using the reactive chemical simulator ChemTOUGH found that 1000 years after the 30 year injection period began approximately 21% of the injected CO2 was permanently sequestered as a mineral, 52% was beneath the ground surface as a gas or dissolved in the groundwater and 17% had leaked to the surface and leakage to the surface was continuing. [Copyright &y& Elsevier]

This paper describes a new suppressor technology for analyzing water samples using United States Environmental Protection Agency (EPA) methods 300.0 and 300.1. The Alltech DS-Plus suppressor improves and simplifies anion analysis in drinking water. In addition to suppressing the carbonate mobile phase and enhancing the analyte signal like conventional ion chromatography (IC) suppressors, the DS-Plus suppressor removes carbonic acid (as dissolved carbon dioxide) from the suppressor effluent before detection (US patent Nos.: 6 444 475; 6 468 804; others pending), lowering the background conductivity to near zero. Anions are detected in water background, improving sensitivity and lowering detection limits. The water-dip often seen with conventional suppressors is greatly reduced, improving fluoride quantification. The DS-Plus suppressor operates continuously without the need for external regenerants or switching valves. The performance of this new suppressor for analyzing water samples has been found to meet the EPA methods specifications. [Copyright &y& Elsevier]

This paper reports on the formation and dissolution of CO2/seawater/ CO2 hydrate composite particles produced during field experiments in Monterey Bay, CA using a CO2 injector system previously developed in the laboratory. The injector consisted of a coflow reactor wherein water was introduced as a jet into liquid CO2, causing vigorous mixing of the two immiscible fluids to promote the formation of CO2 hydrate that is stable at ambient pressures and temperatures typical of ocean depths greater than ∼500 m. Using flow rate ratios of water and CO2 of 1:1 and 5:1, particulate composites of CO2 hydrate/liquid CO2 seawater phases were produced in seawater at depths between 1100 and 1300 m. The resultant composite particles were tracked by a remotely operated vehicle system as they freely traveled in an imaging box that had no bottom or top walls. Results from the field experiments were consistent with laboratory experiments, which were conducted in a 70 L high-pressure vessel to simulate the conditions in the ocean at intermediate depths. The particle velocity and volume histories were monitored and used to calculate the conversion of CO2 into hydrate and its subsequent dissolution rate after release into the ocean. The dissolution rate of the composite particles was found to be higher than that reported for pure CO2 droplets. However, when the rate was corrected to correspond to pure CO2, the difference was very small. Results indicate that a higher conversion of liquid CO2 to CO2 hydrate is needed to form negatively buoyant particles in seawater when compared to freshwater, due primarily to the increased density of the liquid phase but also due to processes involving brine rejection during hydrate formation. [ABSTRACT FROM AUTHOR]

In 1992 the US Environmental Protection Agency (EPA) introduced Energy Star®, a voluntary labeling program designed to identify and promote energy-efficient products, in order to reduce carbon dioxide emissions. Since then, the EPA, now in partnership with the US Department of Energy (DOE), has expanded the program to cover nearly the entire buildings sector, spanning new homes, commercial buildings, residential heating and cooling equipment, major appliances, office equipment, commercial and residential lighting, and home electronics. This paper is based on our experience since 1993 in providing technical support to the Energy Star program. We provide a snapshot of the Energy Star program in the year 2000, including a general overview of the program, its accomplishments, and the possibilities for future development. [Copyright &y& Elsevier]

Many energy systems models have sought to develop pathways for deep decarbonization of the global energy system. Most often, these pathways minimize system costs or greenhouse gas emissions; with few exceptions, they ignore the constraints imposed by political, social, and economic factors that slow transition processes, making them prone to producing implausible decarbonization pathways. This paper integrates a key socio-technical factor—social acceptance of low-carbon nuclear power—into an energy systems model to illustrate how it alters the optimal energy generation mix. The United States was chosen as the example, but the approach itself is designed to be general and applicable to any region of interest. An empirically grounded risk tolerance model is developed to characterize acceptance of nuclear power and estimate an upper-bound deployment limit for the technology. Illustrative scenarios are presented to improve our understanding of how the socio-technical constraints that exist in the real world can alter deep decarbonization pathways. The cost-optimal generation portfolio to achieve net zero CO 2 emissions by 2050 primarily relies on nuclear power. If risk tolerance concerns constrain nuclear deployment to socially acceptable levels, deep decarbonization scenarios are up to 11% more expensive than the reference scenario and require low-carbon options to be available and replace the reduced nuclear share. Results from this novel framework improve our representation of the effect of social acceptance on the adoption and diffusion of energy technologies. They also contribute to a growing literature that seeks to firmly embed the social sciences in climate and energy policy. • Plausible decarbonization pathways must also account for social constraints. • We combine a social risk tolerance model with an energy system optimization model. • We assess the role of social acceptance in constraining nuclear power's deployment. • Social acceptance limits nuclear's share by as much as 71% in CO 2 reduction pathways. • Decision-making can be strengthened with integration of socio-technical analyses. [ABSTRACT FROM AUTHOR]

International environmental agreements have multiplied over the last five decades. We examine the impact of multilateral environmental diplomacy on carbon dioxide (CO2) emissions in the presence of capital formation, renewable energy consumption, and economic growth using the framework of the Environment Kuznets Curve (EKC) and data from the United States from 1980 to 2015. We developed a comprehensive empirical analysis using Zivot–Andrews structural break unit root tests. Co-integration analysis indicates long-run relationships of the variables. The results of the generalized linear models (GLMs) and robust least secure (ROBUSTLS) approach reveal that environmental diplomacy, capital formation, and economic growth deteriorate environmental quality in the long run, while renewable energy consumption improves it. These results support the EKC hypothesis for the United States and suggest that, in the early stages, increased environmental diplomacy stimulates CO2 emissions to a point, after which CO2 emissions start declining with further increases in international commitments and strong diplomatic relationships among countries. Policy implications for the United States are presented. [ABSTRACT FROM AUTHOR]

Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO 2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time and observation-based GPP products. To address this critical gap, here we leverage a state-of-the-art vegetation index, near-infrared reflectance of vegetation (NIR V), along with accurate photosynthetically active radiation (PAR), to produce a SatelLite Only Photosynthesis Estimation (SLOPE) GPP product for the contiguous United States (CONUS). Compared to existing GPP products, the proposed SLOPE product is advanced in its spatial resolution (250 m versus >500 m), temporal resolution (daily versus 8 d), instantaneity (latency of 1 d versus >2 weeks) and quantitative uncertainty (on a per-pixel and daily basis versus no uncertainty information available). These characteristics are achieved because of several technical innovations employed in this study: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIR V (SANIR V) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Cropland Data Layer (CDL) product to predict dynamic C4 crop fraction. Through developing a parsimonious model with only two slope parameters, the proposed SLOPE product explains 85 % of the spatial and temporal variations in GPP acquired from 49 AmeriFlux eddy-covariance sites (324 site years), with a root-mean-square error (RMSE) of 1.63 gC m -2 d -1. The median R2 over C3 and C4 crop sites reaches 0.87 and 0.94, respectively, indicating great potentials for monitoring crops, in particular bioenergy crops, at the field level. With such a satisfactory performance and its distinct characteristics in spatiotemporal resolution and instantaneity, the proposed SLOPE GPP product is promising for biological and environmental research, carbon cycle research, and a broad range of real-time applications at the regional scale. The archived dataset is available at 10.3334/ORNLDAAC/1786 (download page: https://daac.ornl.gov/daacdata/cms/SLOPE%5fGPP%5fCONUS/data/ , last access: 20 January 2021) (Jiang and Guan, 2020), and the real-time dataset is available upon request. [ABSTRACT FROM AUTHOR]

The article discusses the economic impact of the U.S. government's policy governing carbon dioxide pollution. Benefit-cost analysis has become an accepted tool for evaluation of government investment programs in natural resources. Given changing lifestyles, substantial future shifts in technologies and probabilities of drastic world political-social events, any quantitative measures of benefits or costs in 100 years are not subject to better than 2-4 orders of magnitude accuracy and may even switch sign. The carbon dioxide problem, from the standpoint of an economic perspective, has its most interesting elements in terms of intergenerational choice. The reason for it is the anticipated positive economic benefits accruing for several generations and the potential disastrous economic costs that may accrue to generations after that. A drier climate in the Northern Great Plains of the U.S. would cause an increase in the probability of crop failure in any one year. Expected utility of the future depends on available consumption in two possible states of the world. If climate change does not occur, output is a function of capital and fossil fuel availability. Depending on ethical beliefs, different decisions emerge for resolving the carbon dioxide issue.

The recent historical increase in energy-related CO 2 emissions globally have put the United States of America's (USA) transportation sector in the spotlight, courtesy of the significantly high pollutant emissions from this particular sector. Taking a cue from this, this paper follows sustainable development goals of the United Nations, and investigates the impact of biomass energy consumption, fossil fuel energy consumption, and economic growth (GDP) on carbon dioxide (CO 2) emissions in the transportation sector of the USA. In doing so, this study also employs the Gregory-Hansen cointegration, Hatemi-J cointegration, cointegration regression (FMOLS, DOLS, and CCR), and Spectral Breitung-Candelon causality test for the period between 1981Q1 and 2019Q4. The findings reveal that (i) a significant nonlinear cointegration among the environmental quality determinants is observed, using the threshold cointegration test. This test determines the structural breaks endogenously and combines two cointegration tests, namely the Gregory-Hansen Cointegration and Hatemi-J Cointegration tests; (ii) while the use of biomass energy consumption and real GDP have a negative effect on CO 2 emissions in the transportation sector, the rising fossil fuel energy consumption is associated with increasing the CO 2 emissions that are stemming from the transportation sector; (iii) in the long-run, biomass energy consumption, fossil fuel energy consumption, and real GDP cause CO 2 emissions to stem from the transportation sector in the USA at different frequency levels. In general, the current study offers policy insights for the transportation sector of the USA and other similar economies that replicate the same conditions. Image 1 • We explore the driving forces of CO 2 emissions in the transport sector for the USA. • We employ advanced time series econometric techniques for empirical analysis. • Biomass energy and real GDP help to mitigate CO 2 emissions in the transport sector. • Fossil fuel energy has a positive impact on CO 2 emissions in the transport sector. • All variables have a causative relationship with CO 2 emissions in the long-run. [ABSTRACT FROM AUTHOR]

The Representative Concentration Pathway 2.6 (RCP2.6), which is broadly compatible with the Paris Agreement's temperature goal by 1.5–2°C, contains substantial reductions in agricultural non-CO2 emissions besides the deployment of Carbon Dioxide Removal (CDR). Failing to mitigate agricultural methane and nitrous oxide emissions could contribute to an overshoot of the RCP2.6 warming by about 0.4°C. We explore using additional CDR to offset alternative agricultural non-CO2 emission pathways in which emissions either remain constant or rise. We assess the effects on the climate of calculating CDR rates to offset agricultural emission under two different approaches: relying on the 100-year global warming potential conversion metric (GWP100) and maintaining effective radiative forcing levels at exactly those of RCP2.6. Using a reduced-complexity climate model, we find that the conversion metric leads to a systematic underestimation of needed CDR, reaching only around 50% of the temperature mitigation needed to remain on the RCP2.6 track. This is mostly because the metric underestimates, in the near term, forcing from short-lived climate pollutants such as methane. We test whether alternative conversion metrics, the GWP20 and GWP*, are more suitable for offsetting purposes, and found that they both lead to an overestimation of the CDR requirements. Under alternative agricultural emissions pathways, holding to RCP2.6 total radiative forcing requires up to twice the amount of CDR that is already included in the RCP2.6. We examine the costs of this additional CDR, and the effects of internalizing these in several agricultural commodities. Assuming an average CDR cost by $150/tCO2, we find increases in prices of up to 41% for beef, 14% for rice, and 40% for milk in the United States relative to current retail prices. These figures are significantly higher (for beef and rice) under a global scenario, potentially threatening food security and welfare. Although the policy delivers a mechanism to finance the early deployment of CDR, using CDR to offset remaining high emissions may well hit other non-financial constraints and can thus only support, and not substitute, emission reductions. [ABSTRACT FROM AUTHOR]

Twenty-first century citizens are travelling more than ever before. According to experts the upward trend is set to continue, with global travel predicted to increase by around 1.6 per cent each year between now and 2030. This paper discusses the trends of rail transportation for years to come. [ABSTRACT FROM AUTHOR]

If the United States were to adopt a policy to phase out nuclear generation, as has happened recently in other developed countries, what would the environmental and energy-mix implications be? Based on alternative scenarios of nuclear exit that consider the influence of potential policies to limit greenhouse gas emissions, a model of the US and global economy indicates that, under current policy, a US nuclear exit would increase carbon dioxide emissions, and likely raise electricity prices and reduce gross domestic product by relatively small amounts. Those economic impacts would be increased by additional measures to limit carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

In an environment with economic policy uncertainty, the policies of energy efficiency are probably compromised due to weak regulation measures. Inconsistent economic policies may lead to higher energy consumption, which damages the environment. However, works of literature are silent on the role of economic policy uncertainty in carbon emission and energy nexus. Hence, the study is an attempt to investigate the role of economic policy uncertainty in the relationship between energy intensity and carbon dioxide (CO2) emissions in the United States by using annual data spanning from 1985 to 2017. A recent time series method proposed by Jordan and Philips (2018) is employed to get robust and consistent estimation results in the study. Empirical results reveal that (a) higher energy intensity contributes to pollution, (b) economic policy uncertainty adversely affects environmental quality, (c) economic policy uncertainty strengthens the detrimental effect of energy intensity on CO2 emissions. [ABSTRACT FROM AUTHOR]

Production and consumption of nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) are affected by complex interactions of temperature, moisture, and substrate supply, which are further complicated by spatial heterogeneity of the soil matrix. This microsite heterogeneity is often invoked to explain non‐normal distributions of greenhouse gas (GHG) fluxes, also known as hot spots and hot moments. To advance numerical simulation of these belowground processes, we expanded the Dual Arrhenius and Michaelis–Menten model, to apply it consistently for all three GHGs with respect to the biophysical processes of production, consumption, and diffusion within the soil, including the contrasting effects of oxygen (O2) as substrate or inhibitor for each process. High‐frequency chamber‐based measurements of all three GHGs at the Howland Forest (ME, USA) were used to parameterize the model using a multiple constraint approach. The area under a soil chamber is partitioned according to a bivariate log‐normal probability distribution function (PDF) of carbon and water content across a range of microsites, which leads to a PDF of heterotrophic respiration and O2 consumption among microsites. Linking microsite consumption of O2 with a diffusion model generates a broad range of microsite concentrations of O2, which then determines the PDF of microsites that produce or consume CH4 and N2O, such that a range of microsites occurs with both positive and negative signs for net CH4 and N2O flux. Results demonstrate that it is numerically feasible for microsites of N2O reduction and CH4 oxidation to co‐occur under a single chamber, thus explaining occasional measurement of simultaneous uptake of both gases. Simultaneous simulation of all three GHGs in a parsimonious modeling framework is challenging, but it increases confidence that agreement between simulations and measurements is based on skillful numerical representation of processes across a heterogeneous environment. [ABSTRACT FROM AUTHOR]

Carbon-based payments for ecosystem services solely consider afforestation and reforestation to assess sequestration. However, political ecology researchers demonstrate that tropical forests are complex socioecological systems where humans and institutions play an integral role in shaping landscapes. The current framing overlooks the net effect of traditional subsistence agriculturalists leaving behind low emission lifestyles, despite the likelihood of a significant increase in per capita emissions over time. In this case study, we use the history of forest use in the Pueblos Mancomunados—a commonwealth of indigenous communities in Oaxaca, Mexico—to explore sequestration through a socioecological systems lens. As negative emissions programs consider afforestation, we triangulated semistructured interviews, an unsupervised GIS classification of land cover, and a review of carbon dioxide emissions to consider out-migration, abandonment, and lifestyle change. We find that communities are struggling to maintain livelihoods as migration to urban centers and the United States continues. Meanwhile, spatial analysis revealed 800 ha of afforestation. Our analysis of out-migration scenarios and per capita emissions changes identified a tipping point in which no net-sequestration would occur from afforestation due to the changing lifestyles of the migrants and recommend improved local development to avoid this form of "leakage" when assessing global carbon stocks. [ABSTRACT FROM AUTHOR]

The current energy portfolio of the United States is exposed to significant risk, which depends on the price volatility of the energy sources. This paper focuses on the composition of energy portfolios for the energy sector of the United States and possible solutions to optimize this investment. The study utilizes the modern portfolio theory mean-variance approach, a risk-return analysis, to compose the efficient frontier of portfolios in which the risk is minimized for a given return. The performance of each energy portfolio, consisting of oil, coal, natural gas, nuclear energy, and renewable energy, is measured using the Sharpe Ratio and compared to the existing portfolio. Using future prices of fuels and accounting for external costs, the study provides further evidence that the current energy portfolio of the United States is not efficient. In addition, the study shows how including the cost of pollution, measured by the intensity of carbon emissions, changes the energy source allocation within the portfolio by including less carbon-intensive substances. The study implies that further diversification of the energy sector by including investment in hydroelectric energy generation technologies may decrease our dependence on more volatile sources of energy and consequently reduce the possibility of energy supply interruption from commodity price volatility. This proposes that the government focus on implementing a strategy to facilitate the introduction of renewable energy into our energy portfolio. The shift away from an infrastructure heavily dependent on fossil fuels towards one with more investment in renewable energy can be achieved by granting subsidies for renewable energy technologies and by implementing appropriate emissions prices to account for external energy generation costs. [ABSTRACT FROM AUTHOR]

In this article, we propose a stochastic formulation of mass balances that impose physical constraints on production technologies. The estimation of the model involves a composed error term structure that is commonly applied in the literature on stochastic frontier analysis of productive efficiency. Moreover, we discuss how ordinary least squares and maximum likelihood methods can be used to estimate emission coefficients based on the proposed model and compare the results to estimates based on linear programming techniques from input–output analysis. In contrast to previous approaches, our model allows one to estimate the physical limitations to production possibilities in the presence of statistical noise and depends on substantially weaker data requirements. We apply our approach to estimate emission coefficients for sulfur dioxide and carbon dioxide using a sample of fossil‐fueled power plants in the United States. [ABSTRACT FROM AUTHOR]

Greatly enhanced atmospheric carbon dioxide (CO2) levels relative to well-mixed marine air are observed during periods of offshore winds at coastal sensor platforms in Monterey Bay, California, USA. The highest concentrations originate from urban and agricultural areas, are driven by diurnal winds, and peak in the early morning. These enhanced atmospheric levels can be detected across a ~100km wide nearshore area and represent a significant addition to total oceanic CO2 uptake. A global estimate puts the added sea-air flux of CO2 from these greatly enhanced atmospheric CO2 levels at 25 million tonnes, roughly 1% of the ocean’s annual CO2 uptake. The increased uptake over the 100 km coastal swath is of order 20%, indicating a potentially large impact on ocean acidification in productive coastal waters. [ABSTRACT FROM AUTHOR]

Many countries have passed environmental laws aiming at preserving natural ecosystems, such as the Endangered Species Act of 1973 in the United States. Although those regulations seem to have improved preservation, they may have had unintended consequences in energy production. Here we show that while environmental constraints on hydropower may have preserved the wilderness and wildlife by restricting the development of hydroelectric projects, they led to more greenhouse gas emissions. Environmental regulations gave rise to a replacement of hydropower, which is a renewable, relatively low-emitting source of energy, with conventional fossil-fuel power, which is highly polluting. Our estimates indicate that, on average, each megawatt of fossil fuel power-generating capacity added to the grid because of environmental constraints on hydropower development led to an increase in annual carbon dioxide emissions of about 1,400 tons. Environmental regulations focusing only on the preservation of ecosystems appear to have encouraged electric utilities to substitute dirtier fuels for hydropower in electricity generation. [ABSTRACT FROM AUTHOR]

Climate change is affecting the growth, phenology, and distribution of species across northeastern United States. In response to these changes, some species have been adversely impacted while others have benefited. One species that has benefited from climate change, historically and in response to experimental treatments, is common ragweed (Ambrosia artemisiifolia), a widely distributed annual weed and a leading cause of hay fever in North America. To better understand how climate change may affect the distribution of common ragweed, we built a maximum entropy (Maxent) predictive model using climate and bioclimatic data and over 700 observations across the eastern U.S. Our model performed well with an AUC score of 0.765 using four uncorrelated variables, including precipitation seasonality, mean diurnal temperature range, August precipitation, and January maximum temperature. After building and testing our model, we then projected potential future common ragweed distribution using a suite of 13 global climate models (GCMs) under two future greenhouse gas scenarios for mid and late-century. In addition to providing georeferenced hot spots of potential future expansion, we also provide a metric of confidence by evaluating the number of GCMs that agree. We show a substantial contraction of common ragweed in central Florida, southern Appalachian Mountains, and northeastern Virginia and areas of potential expansion at the northern margins of its current distribution, notably in northeastern U.S. However, the vast majority of this increase is projected to occur by mid-century and may be moderated somewhat by the 2070s, implying that common ragweed may be sensitive to climatic variability. Although other factors and modeling approaches should be explored, we offer preliminary insight into where common ragweed might be a new concern in the future. Due to the health impacts of ragweed, local weed control boards may be well advised to monitor areas of expansion and potentially increase eradication efforts. [ABSTRACT FROM AUTHOR]

Discusses the political opposition to carbon sequestration research by the United States government. The assertion that removing carbon dioxide from the atmosphere is as important as controlling emissions; Recommendations of the US President's Committee of Advisors on Science and Technology to the Department of Energy to increase funding; The belief that the US political climate is hindering research.

The efflux of CO2 from the soil surface can vary markedlyin magnitude both in time and space and its correct determination iscrucial in many ecological studies. In this paper, we report resultsof field measurements, using an open-top dynamic chamber, of soil CO2 efflux in a mature Florida slash pine (Pinus elliottii Engelm. var.elliottii) plantation. The daily average efflux was 0.217 mg CO2 m-2s-1 in the autumn and 0.087 mg CO2 m-2s-1 in the winter. Soil temperature, which accounts for most of the temporal variability in CO2 efflux, is by far the most influential factor controlling soil respiration rate and its temporal variation. The CO2 efflux in the slash pine plantation is highly spatially variable and effluxes from the soil under palmetto is significantly higher than that from the open floor. The CO2 efflux generally increases with increase in soil fine root biomass,litter and humus amount on the forest floor but is inversely relatedto the amount of organic matter in the mineral soil. The spatial variation in CO2 efflux can be well characterised by a simplemultiple regression model incorporating live and dead biomass and soil total porosity as predictor variables. Understorey plants, mostly Serenoa repens, are an important component of the C cycle and the major contributor to the spatial heterogeneity of soil CO2 efflux. The influence of understorey plants on soil respiration is probably via two approaches: increasing litterfall and root metabolism, both consequently stimulating microbial activity in the mineral soil. [ABSTRACT FROM AUTHOR]

This paper provides an empirical analysis of the impact of various influences on carbon dioxide emissions. It incorporates methodologicalrefinements of input-output structural decomposition analysis, whichis the examination of economic change by means of a set of comparative static variations in key parameters of I-O tables. The analysis isperformed using a two-tiered KLEM model, which allows for estimationof substitution and technological change effects within and between input aggregates. The model is used to decompose the sources of change in CO2 emissions in the U.S. over the 1972-82 timeframe using hybrid energy/value tables for the initial and terminal years. Results show the significant effect of substitution within the energysector and between energy and other inputs as the leading causes of the decline in carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

This paper is stimulated by the debate in the US about optimal abatement paths, in particular recent claims that it would be economicallypreferable to defer such abatement action, in favour of measures that support technology development but do not affect emission trends for many years. This paper categorises the various economic issues involved and concludes that for each economic argument that has been advanced to justify deferring emission constraints, there are countervailing economic arguments that could be used in support of rapid near-term emissions abatement. Rational policy lies between these extremes. A policy of deferring all emissions abatement exposes economic systems and industries, as well as the environment, to significantly greater costs and risks than those arising from a more balanced approach. Furthermore the modelling studies that have been used to justify deferring emissions abatement do so because they embody the economic factors favourable to delay and largely neglect the countervailing issues,to the point where they cannot be considered as relevant to a balanced assessment of the issues relating to economically optimal abatement timing. [ABSTRACT FROM AUTHOR]

The ice‐covered period on lakes in the northern hemisphere has often been neglected or assumed to have less importance relative to the open water season. However, recent studies challenge this convention, suggesting that the winter period is more dynamic than previously thought. In this review, we synthesize the current understanding of under‐ice carbon dioxide (CO2) and methane (CH4) dynamics, highlighting the annual importance of CO2 and CH4 emissions from lakes at ice‐melt. We compiled data from 25 studies that showed that the ice‐melt period represents 17% and 27% of the annual CO2 and CH4 emissions, respectively. We also found evidence that the magnitude and type of emission (i.e., CO2 and CH4) varies with characteristics of lakes including geographic location, lake morphometry, and physicochemical conditions. The scarcity of winter and spring carbon data from northern lakes represents a major gap in our understanding of annual budgets in these lakes and calls for future research during this key period. [ABSTRACT FROM AUTHOR]

Bioenergy with carbon capture and storage (BECCS) is a negative-emissions technology that may play a crucial role in climate change mitigation. BECCS relies on the capture and sequestration of carbon dioxide (CO2) following bioenergy production to remove and reliably sequester atmospheric CO2. Previous BECCS deployment assessments have largely overlooked the potential lack of spatial colocation of suitable storage basins and biomass availability, in the absence of long-distance biomass and CO2 transport. These conditions could constrain the near-term technical deployment potential of BECCS due to social and economic barriers that exist for biomass and CO2 transport. This study leverages biomass production data and site-specific injection and storage capacity estimates at high spatial resolution to assess the near-term deployment opportunities for BECCS in the United States. If the total biomass resource available in the United States was mobilized for BECCS, an estimated 370 Mt CO2⋅y-1 of negative emissions could be supplied in 2020. However, the absence of long-distance biomass and CO2 transport, as well as limitations imposed by unsuitable regional storage and injection capacities, collectively decrease the technical potential of negative emissions to 100 Mt CO2⋅y-1. Meeting this technical potential may require large-scale deployment of BECCS technology in more than 1,000 counties, as well as widespread deployment of dedicated energy crops. Specifically, the Illinois basin, Gulf region, and western North Dakota have the greatest potential for near-term BECCS deployment. Highresolution spatial assessment as conducted in this study can inform near-term opportunities that minimize social and economic barriers to BECCS deployment. [ABSTRACT FROM AUTHOR]

The study aims to combine the autoregressive distributed lag (ARDL) cointegration framework with smooth transition autoregressive (STAR)-type nonlinear econometric models for causal inference. Further, the proposed STAR distributed lag (STARDL) models offer new insights in terms of modeling nonlinearity in the long- and short-run relations between analyzed variables. The STARDL method allows modeling and testing nonlinearity in the short-run and long-run parameters or both in the short- and long-run relations. To this aim, the relation between CO emissions and economic growth rates in the USA is investigated for the 1800-2014 period, which is one of the largest data sets available. The proposed hybrid models are the logistic, exponential, and second-order logistic smooth transition autoregressive distributed lag (LSTARDL, ESTARDL, and LSTAR2DL) models combine the STAR framework with nonlinear ARDL-type cointegration to augment the linear ARDL approach with smooth transitional nonlinearity. The proposed models provide a new approach to the relevant econometrics and environmental economics literature. Our results indicated the presence of asymmetric long-run and short-run relations between the analyzed variables that are from the GDP towards CO emissions. By the use of newly proposed STARDL models, the results are in favor of important differences in terms of the response of CO emissions in regimes 1 and 2 for the estimated LSTAR2DL and LSTARDL models. [ABSTRACT FROM AUTHOR]

Cotton is a natural fiber that takes up carbon dioxide from the environment when grown; however, it requires various resources to be cultivated in a financially viable way. Resources such as fertilizer, pesticides, herbicides, and irrigation water can create environmental impacts as well as present significant costs to the grower. Understanding the efficacy of technologies and grower practices is an important aspect of developing best practices and guiding future research. To better understand the grower needs, practices, and resource use efficiency, a survey was conducted in 2015 with 925 U.S. cotton grower respondents. This survey gathered data on field performance, pest pressures, growing practices, and other parameters that were used to examine the resources used per pound of cotton lint as well as estimate the greenhouse gas emissions and energy use from cotton cultivation. In general, growers who used various precision agricultural technologies reported higher performing fields with higher resource use efficiencies than non-precision technology adopters. [ABSTRACT FROM AUTHOR]

The article reports on the results of a workshop sponsored by three United States federal agencies regarding the impact of carbon dioxide emissions on coral reefs. The paper entitled "Impacts of Ocean Acidification on Coral Reefs and Other Marine Calcifiers," indicate that calcification rates in coral could decrease by as much as 60 percent within the 21st century as a direct result of the increasingly acidic ocean condition.

Reducing carbon dioxide (CO2) emissions from power plants can have important “co-benefits” for public health by reducing emissions of air pollutants. Here, we examine the costs and health co-benefits, in monetary terms, for a policy that resembles the U.S. Environmental Protection Agency’s Clean Power Plan. We then examine the spatial distribution of the co-benefits and costs, and the implications of a range of cost assumptions in the implementation year of 2020. Nationwide, the total health co-benefits were $29 billion 2010 USD (95% CI: $2.3 to $68 billion), and net co-benefits under our central cost case were $12 billion (95% CI: -$15 billion to $51 billion). Net co-benefits for this case in the implementation year were positive in 10 of the 14 regions studied. The results for our central case suggest that all but one region should experience positive net benefits within 5 years after implementation. [ABSTRACT FROM AUTHOR]

The article discusses the projected increases in regional temperatures and atmospheric carbon dioxide CO2 levels, among the several factors influencing plant growth and pollen production, which could mean a rise in the number of people impacted by seasonal allergies. Topics include Leonard Bielory of the Rutgers University Center of Environmental Prediction, Kate Weinberger of Brown University, and Lewis Ziska of U.S. Department of Agriculture (USDA).

The article focuses on the approaches in lowering the carbon footprint of health care sector as they contribute to global climate change. Topics include the widely varying impacts of specific practices to climate change, the role of life cycle analysis (LCA) as a transformative tool in promoting sustainability in health care, and the technical and operational considerations in promoting sustainable practices in health care.

We used a simple, systematic data-analytics approach to determine the relative linkages of different climate and environmental variables with the canopy-level, half-hourly CO fluxes of US deciduous forests. Multivariate pattern recognition techniques of principal component and factor analyses were utilized to classify and group climatic, environmental, and ecological variables based on their similarity as drivers, examining their interrelation patterns at different sites. Explanatory partial least squares regression models were developed to estimate the relative linkages of CO fluxes with the climatic and environmental variables. Three biophysical process components adequately described the system-data variances. The 'radiation-energy' component had the strongest linkage with CO fluxes, whereas the 'aerodynamic' and 'temperature-hydrology' components were low to moderately linked with the carbon fluxes. On average, the 'radiation-energy' component showed 5 and 8 times stronger carbon flux linkages than that of the 'temperature-hydrology' and 'aerodynamic' components, respectively. The similarity of observed patterns among different study sites (representing gradients in climate, canopy heights and soil-formations) indicates that the findings are potentially transferable to other deciduous forests. The similarities also highlight the scope of developing parsimonious data-driven models to predict the potential sequestration of ecosystem carbon under a changing climate and environment. The presented data-analytics provides an objective, empirical foundation to obtain crucial mechanistic insights; complementing process-based model building with a warranted complexity. Model efficiency and accuracy ( R = 0.55-0.81; ratio of root-mean-square error to the observed standard deviations, RSR = 0.44-0.67) reiterate the usefulness of multivariate analytics models for gap-filling of instantaneous flux data. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilizer use in managed forest ecosystems is increasing in the United States and worldwide to enhance social, economical and environmental services. However, the effects of N-fertilization on production and consumption of greenhouse gases (GHGs), especially carbon dioxide (CO), methane (CH), and nitrous oxide (NO) in managed forest ecosystems are poorly understood, unlike in agriculture where effects are well documented. Therefore, a review of the available literature was conducted to comprehend the effects of N-fertilization on CO, CH and NO emissions in managed forest ecosystems to summarize sources, sinks, and controlling factors, as well as potential mitigation strategies and research gaps to reduce GHG emissions. This review clearly identifies the importance of N-fertilizer management practices on CO, CH and NO emissions. Potential N management practices to mitigate GHG emissions in managed forest ecosystems include improving N uptake efficiency, identifying and managing spatial variation in soil fertility, using the right fertilizer source at the right time, adopting appropriate methods of N-fertilizer application, and introducing nitrification/denitrification inhibitors. Nitrogen-fertilizer response is affected by soil physical (e.g., moisture, drainage, bulk density, and texture), chemical (e.g., nutrient availability, labile carbon, soil pH, and C/N ratio) and local climatic factors (e.g., temperature, relative humidity, and rainfall). Therefore, the interactions of these factors on GHG emissions need to be considered while evaluating N-fertilizer management practices. Existing studies are often limited, focusing primarily on temperate forest ecosystems, lacking estimation of net emissions considering all three predominant soil-derived GHGs, and were often conducted on a small scale, making upscaling challenging. Therefore, large-scale studies conducted in diverse climates, evaluating cumulative net emissions, are needed to better understand N-fertilization effects on GHG emissions and develop mitigation strategies. Mitigation strategies and research gaps have also been identified, which require the collaborative efforts of forest owners, managers, and scientists to increase adoption of N-fertilization best management practices and understand the importance of N-fertilizer management strategies in reducing emissions and enhancing the net GHG sink potential for managed forest ecosystems. [ABSTRACT FROM AUTHOR]

In order to plan for global changing climate experiments are being conducted in many countries, but few have monitored the effects of the climate change treatments (warming, elevated CO2) on the experimental plot microclimate. During three years of an eight year study with year-round feedback-controlled infra-red heater warming (1.5/3.0°C day/night) and growing season free-air CO2 enrichment (600 ppm) in the mixed-grass prairie of Wyoming, USA, we monitored soil, leaf, canopy-air, above-canopy-air temperatures and relative humidity of control and treated experimental plots and evaluated ecologically important temperature differentials. Leaves were warmed somewhat less than the target settings (1.1 & 1.5°C day/night) but soil was warmed more creating an average that matched the target settings extremely well both during the day and night plus the summer and winter. The site typically has about 50% bare or litter covered soil, therefore soil heat transfer is more critical than in dense canopy ecosystems. The Wyoming site commonly has strong winds (5 ms-1 average) and significant daily and seasonal temperature fluctuations (as much as 30°C daily) but the warming system was nearly always able to maintain the set temperatures regardless of abiotic variation. The within canopy-air was only slightly warmed and above canopy-air was not warmed by the system, therefore convective warming was minor. Elevated CO2 had no direct effect nor interaction with the warming treatment on microclimate. Relative humidity within the plant canopy was only slightly reduced by warming. Soil water content was reduced by warming but increased by elevated CO2. This study demonstrates the importance of monitoring the microclimate in manipulative field global change experiments so that critical physiological and ecological conclusions can be determined. Highly variable energy demand fluctuations showed that passive IR heater warming systems will not maintain desired warming for much of the time. [ABSTRACT FROM AUTHOR]

Accurate spatial estimation of forest carbon stocks and their spatial uncertainties at local, regional, national, and global scales is a critical step in global carbon cycle modeling and management. This study aimed at enhancing the methods that are currently used in this area by combining plot data from the forest inventory and analysis program of the U.S. Forest Service and free landsat thematic mapper image data. Three mapping methods including linear regression, sequential Gaussian co-simulation, and block co-simulation algorithm were compared with respect to the accuracy of forest carbon stock estimates obtained for a study area in Southern Illinois, USA. The results indicated that although the linear regression resulted in smaller prediction errors than the sequential Gaussian co-simulation and the block co-simulation approaches, it also produced both negative and unreasonably large estimates, which is a serious drawback. Moreover, the sequential Gaussian co-simulation and the block co-simulation produced not only accurate carbon predictions, but also uncertainties for the local estimates. In addition, the block co-simulation approach scaled up both forest carbon stocks and the input uncertainties from finer to coarser spatial resolutions as is required for mapping forest carbon at national and global scales. Thus, the co-simulation and block co-simulation algorithms resolved an important current methodological challenge. [ABSTRACT FROM AUTHOR]

While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM would yield economic benefits in the range of $6 to $30 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $198 per metric ton of CO in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity. [ABSTRACT FROM AUTHOR]

Temperate- and high-latitude forests have been shown to contribute a carbon sink in the Northern Hemisphere, but fewer studies have addressed the carbon balance of the subtropical forests. In the present study, we integrated eddy covariance observations established in the 1990s and 2000s to show that East Asian monsoon subtropical forests between 20°N and 40°N represent an average net ecosystem productivity (NEP) of 362 ± 39 g C m-2 yr-1 (mean ± 1 SE). This average forest NEP value is higher than that of Asian tropical and temperate forests and is also higher than that of forests at the same latitudes in Europe- Africa and North America. East Asian monsoon subtropical forests have comparable NEP to that of subtropical forests of the southeastern United States and intensively managed Western European forests. The total NEP of East Asian monsoon subtropical forests was estimated to be 0.72 ± 0.08 Pg C yr-1, which accounts for 8% of the global forest NEP. This result indicates that the role of subtropical forests in the current global carbon cycle cannot be ignored and that the regional distributions of the Northern Hemisphere's terrestrial carbon sinks are needed to be reevaluated. The young stand ages and high nitrogen deposition, coupled with sufficient and synchronous water and heat availability, may be the primary reasons for the high NEP of this region, and further studies are needed to quantify the contribution of each underlying factor. [ABSTRACT FROM AUTHOR]

The social cost of carbon (SCC) is an important concept for understanding and implementing climate change policies. This term represents the economic cost caused by an additional ton of carbon dioxide emissions (or more succinctly carbon) or its equivalent. The present study describes the development of the concept, provides examples of its use in current US regulator policies, examines its analytical background, and estimates the SCC using an updated integrated assessment model, the DICE-2013R model. The study estimates that the SCC is $18.6 per ton of CO2 in 2005 US dollars and international prices for the current period (2015). For the central case, the real SCC grows at 3% per year over the period to 2050. The major open issues concerning the SCC continue to be the appropriate discount rate, the potential for catastrophic damages, the impact of incomplete harmonization of abatement policies, and the effects of distortionary taxes. [ABSTRACT FROM AUTHOR]

Annual CO2emission tallies for 210 coal-fired power plants during 2009 were more accurately calculated from fuel consumption records reported by the U.S. Energy Information Administration (EIA) than measurements from Continuous Emissions Monitoring Systems (CEMS) reported by the U.S. Environmental Protection Agency. Results from these accounting methods for individual plants vary by ± 10.8%. Although the differences systematically vary with the method used to certify flue-gas flow instruments in CEMS, additional sources of CEMS measurement error remain to be identified. Limitations of the EIA fuel consumption data are also discussed. Consideration of weighing, sample collection, laboratory analysis, emission factor, and stock adjustment errors showed that the minimum error for CO2emissions calculated from the fuel consumption data ranged from ± 1.3% to ± 7.2% with a plant average of ± 1.6%. This error might be reduced by 50% if the carbon content of coal delivered to U.S. power plants were reported. [ABSTRACT FROM PUBLISHER]